Enterprise AI agent platforms combine agent frameworks, marketplaces, and governance tooling to automate recurrent accounting, regulatory compliance and client‑onboarding tasks with traceability and human oversight. As of 2026, organizations are adopting multi‑agent orchestrations and no‑code/low‑code builders to speed integrations with ERPs, KYC/AML checks and bookkeeping pipelines while responding to tighter regulatory expectations (model auditability, data residency and vendor governance). Key platform types include: agent frameworks and orchestration layers (IBM watsonx Assistant, MindStudio, StackAI, Relevance AI) that let teams design, test and deploy assistants and multi‑agent workflows; foundation model and infra providers (Mistral AI, Vertex AI) offering scalable LLMs and production tooling; governance and observability vendors (Monitaur, Xilos) that centralize policy, monitoring and vendor risk; and specialist CX/outsourcing models (Crescendo.ai) that pair agentic AI with human experts for outcome guarantees. Workspaces and automation hubs (Notion, Anakin.ai) provide lightweight integrations and document/knowledge plumbing for onboarding and bookkeeping use cases. Practical priorities are explainability for audits, immutable audit trails for ledger‑adjacent actions, granular access controls, and vendor/model risk management. Teams balance no‑code speed with developer extensibility, preferring platforms that provide connectors to accounting systems, data governance APIs and built‑in monitoring. The result is a maturing ecosystem where enterprise buyers evaluate not just model quality but governance, integration breadth and operational observability when selecting AI agent platforms for accounting, compliance and client onboarding.